Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/bladeofgod/flutter-ai-harness/review-batchgit clone --depth 1 https://github.com/bladeofgod/flutter-ai-harnessWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/bladeofgod/flutter-ai-harness/review-batch)<a href="https://agentmods.dev/commands/bladeofgod/flutter-ai-harness/review-batch"><img src="https://agentmods.dev/badge/commands/bladeofgod/flutter-ai-harness/review-batch.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.00465 |
| Opus 5 | $0.00016 | $0.00233 |
| Sonnet 5 | $0.00006 | $0.00093 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
review-batch scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
需要对一组已完成任务做聚合检查时执行批次审查。用户必须明确给出本次纳入的记录以及 diff 范围；缺失时停止并请求补充，不维护或猜测批次 baseline。
- 只读取参数中明确指定的
docs/tasks/done/任务卡、Review 报告和测试证据，以及这些记录直接引用的产物。 - 按用户指定的 Git Range、工作树或文件列表审查聚合改动，不从任务时间、当前 HEAD 或历史报告推断范围。
- 对用户明确纳入任务的
workKinds求并集，按/execute-tasks的固定映射选择普通 Review Profile；documentation、planning仍只在没有实质 Profile 时选择contract-reviewer。多个 Profile 审查同一 冻结候选且相互不读取结论；检查跨卡回归：依赖方向、重复抽象、Entity 不一致、DI 顺序、Route 冲突、 平台契约漂移、Harness 生命周期、生成文件过期和端到端覆盖缺口。 - 运行
make check，并根据聚合影响面运行集成测试或原生构建。 - 写入
docs/reviews/<batch-slug>-summary.md，包含实际运行的 Profile、带ownerProfile的 P0/P1/P2、 任务覆盖、验证证据、未验证平台和发布建议。 - 不修改实现；需要修复时，等待用户明确调用
/fix-review-findings <report-path>。
除非问题在集成层重新出现，不重复已经解决的单卡问题。只有 P0/P1 清零且所有跳过验证都已说明，批次审查才可通过。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 20 lines · 32 tokens per session scan A a517caf32446
review-batch is a command published in the GitHub repository bladeofgod/flutter-ai-harness (113 stars, last pushed 3d ago), licensed MIT. It adds 32 tokens to every session and 465 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.